Speaker
Description
Cloud computing is an increasingly important platform for scientific collaboration, interactive analysis, and reproducible research. However, deploying and maintaining cloud infrastructure often requires familiarity with a rapidly growing ecosystem of tools, creating a significant barrier for many scientists and research software engineers. A reproducible deployment makes it practical to rapidly create new science environments for collaborations, workshops, or project-specific efforts, while leveraging cloud bursting to temporarily scale compute resources for computationally intensive analyses without maintaining permanently provisioned infrastructure. HelioCloud was designed to reduce this complexity by providing a reproducible, open-source science cloud built on modern cloud-native technologies (OpenTofu, Helm, Kubernetes) while exposing only the concepts necessary for day-to-day operation. We discuss how researchers and developers can confidently contribute to and operate a science cloud without becoming cloud experts, while taking advantage of scalable computing, simplified deployments, and direct access to large scientific datasets.